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bert_uncased_L-4_H-768_A-12_massive
This model is a fine-tuned version of google/bert_uncased_L-4_H-768_A-12 on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 0.5747
- Accuracy: 0.8898
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 33
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.1636 | 1.0 | 180 | 0.9552 | 0.7983 |
| 0.7696 | 2.0 | 360 | 0.5934 | 0.8539 |
| 0.4303 | 3.0 | 540 | 0.4996 | 0.8721 |
| 0.2708 | 4.0 | 720 | 0.4900 | 0.8780 |
| 0.1756 | 5.0 | 900 | 0.4886 | 0.8780 |
| 0.113 | 6.0 | 1080 | 0.5020 | 0.8829 |
| 0.076 | 7.0 | 1260 | 0.5211 | 0.8810 |
| 0.0517 | 8.0 | 1440 | 0.5452 | 0.8864 |
| 0.035 | 9.0 | 1620 | 0.5516 | 0.8883 |
| 0.026 | 10.0 | 1800 | 0.5652 | 0.8864 |
| 0.0193 | 11.0 | 1980 | 0.5696 | 0.8869 |
| 0.0156 | 12.0 | 2160 | 0.5592 | 0.8888 |
| 0.0134 | 13.0 | 2340 | 0.5762 | 0.8893 |
| 0.0103 | 14.0 | 2520 | 0.5726 | 0.8883 |
| 0.0107 | 15.0 | 2700 | 0.5747 | 0.8898 |
Framework versions
- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.1
